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Ganapathy K, Lam C, Tsukuda J, Sargon A, Nava A, Harms P, Shen A, Barnard G, Misaghi S. SPEED-MODE cell line development (CLD): Reducing Chinese hamster ovary (CHO) CLD timelines via earlier suspension adaptation and maximizing time spent in the exponential growth phase. Biotechnol Prog 2024; 40:e3479. [PMID: 38716635 DOI: 10.1002/btpr.3479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 04/23/2024] [Accepted: 04/25/2024] [Indexed: 10/15/2024]
Abstract
Chinese hamster ovary (CHO) cells are the preferred system for expression of therapeutic proteins and the majority of all biotherapeutics are being expressed by these cell lines. CHO expression systems are readily scalable, resistant to human adventitious agents, and have desirable post-translational modifications, such as glycosylation. Regardless, drug development as a whole is a very costly, complicated, and time-consuming process. Therefore, any improvements that result in reducing timelines are valuable and can provide patients with life-saving drugs earlier. Here we report an effective method (termed SPEED-MODE, herein) to speed up the Cell line Development (CLD) process in a targeted integration (TI) CHO CLD system. Our findings show that (1) earlier single cell cloning (SCC) of transfection pools, (2) speeding up initial titer screening turnaround time, (3) starting suspension adaptation of cultures sooner, and (4) maximizing the time CHO cultures spend in the exponential growth phase can reduce CLD timelines from ~4 to ~3 months. Interestingly, SPEED-MODE timelines closely match the theoretical minimum timeline for CHO CLD assuming that CHO cell division is the rate limiting factor. Clones obtained from SPEED-MODE CLD yielded comparable titer and product quality to those obtained via a standard CLD process. Hence, SPEED-MODE CLD is advantageous for manufacturing biotherapeutics in an industrial setting as it can significantly reduce CLD timelines without compromising titer or product quality.
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Affiliation(s)
- Kavya Ganapathy
- Cell Culture and Bioprocess Operations Department, Genentech Inc., South San Francisco, California, USA
| | - Cynthia Lam
- Cell Culture and Bioprocess Operations Department, Genentech Inc., South San Francisco, California, USA
| | - Joni Tsukuda
- Cell Culture and Bioprocess Operations Department, Genentech Inc., South San Francisco, California, USA
| | - Alyssa Sargon
- Cell Culture and Bioprocess Operations Department, Genentech Inc., South San Francisco, California, USA
| | - Adrian Nava
- Cell Culture and Bioprocess Operations Department, Genentech Inc., South San Francisco, California, USA
| | - Peter Harms
- Cell Culture and Bioprocess Operations Department, Genentech Inc., South San Francisco, California, USA
| | - Amy Shen
- Cell Culture and Bioprocess Operations Department, Genentech Inc., South San Francisco, California, USA
| | - Gavin Barnard
- Cell Culture and Bioprocess Operations Department, Genentech Inc., South San Francisco, California, USA
| | - Shahram Misaghi
- Cell Culture and Bioprocess Operations Department, Genentech Inc., South San Francisco, California, USA
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2
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Cai J, Wang Q, Wang C, Deng Y. Research on cell detection method for microfluidic single cell dispensing. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:3970-3982. [PMID: 36899612 DOI: 10.3934/mbe.2023185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Single cell dispensing techniques mainly include limiting dilution, fluorescent-activated cell sorting (FACS) and microfluidic approaches. Limiting dilution process is complicated by statistical analysis of clonally derived cell lines. Flow cytometry and conventional microfluidic chip methods utilize excitation fluorescence signals for detection, potentially causing a non-negligible effect on cell activity. In this paper, we implement a nearly non-destructive single-cell dispensing method based on object detection algorithm. To realize single cell detection, we have built automated image acquisition system and then employed PP-YOLO neural network model as detection framework. Through architecture comparison and parameter optimization, we select ResNet-18vd as backbone for feature extraction. We train and evaluate the flow cell detection model on train and test set consisting of 4076 and 453 annotated images respectively. Experiments show that the model inference an image of 320 × 320 pixels at least 0.9 ms with the precision of 98.6% on a NVidia A100 GPU, achieving a good balance of detection speed and accuracy.
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Affiliation(s)
- Junjing Cai
- Jihua Institute of Biomedical Engineering Technology, Jihua Laboratory, Foshan 528200, China
- School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
| | - Qiwei Wang
- Jihua Institute of Biomedical Engineering Technology, Jihua Laboratory, Foshan 528200, China
| | - Ce Wang
- Jihua Institute of Biomedical Engineering Technology, Jihua Laboratory, Foshan 528200, China
| | - Yu Deng
- School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
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3
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Tejwani V, Chaudhari M, Rai T, Sharfstein ST. High-throughput and automation advances for accelerating single-cell cloning, monoclonality and early phase clone screening steps in mammalian cell line development for biologics production. Biotechnol Prog 2021; 37:e3208. [PMID: 34478248 DOI: 10.1002/btpr.3208] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/30/2021] [Accepted: 09/01/2021] [Indexed: 12/13/2022]
Abstract
Mammalian cell line development is a multistep process wherein timelines for developing clonal cells to be used as manufacturing cell lines for biologics production can commonly extend to 9 months when no automation or modern molecular technologies are involved in the workflow. Steps in the cell line development workflow involving single-cell cloning, monoclonality assurance, productivity and stability screening are labor, time and resource intensive when performed manually. Introduction of automation and miniaturization in these steps has reduced the required manual labor, shortened timelines from months to weeks, and decreased the resources needed to develop manufacturing cell lines. This review summarizes the advances, benefits, comparisons and shortcomings of different automation platforms available in the market for rapid isolation of desired clonal cell lines for biologics production.
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Affiliation(s)
- Vijay Tejwani
- Biotechnology R&D, Clone Development Team, Lupin Limited, Pune, India
| | - Minal Chaudhari
- Biotechnology R&D, Clone Development Team, Lupin Limited, Pune, India
| | - Toyaj Rai
- Biotechnology R&D, Clone Development Team, Lupin Limited, Pune, India
| | - Susan T Sharfstein
- College of Nanoscale Science and Engineering, SUNY Polytechnic Institute, Albany, New York, USA
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4
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Diep J, Le H, Le K, Zasadzinska E, Tat J, Yam P, Zastrow R, Gomez N, Stevens J. Microfluidic chip-based single-cell cloning to accelerate biologic production timelines. Biotechnol Prog 2021; 37:e3192. [PMID: 34323013 PMCID: PMC9285370 DOI: 10.1002/btpr.3192] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 07/06/2021] [Accepted: 07/12/2021] [Indexed: 12/20/2022]
Abstract
Cell line development (CLD) represents a critical, yet time‐consuming, step in the biomanufacturing process as significant resources are devoted to the scale‐up and screening of several hundreds to thousands of single‐cell clones. Typically, transfected pools are fully recovered from selection and characterized for growth, productivity, and product quality to identify the best pools suitable for single‐cell cloning (SCC) using limiting dilution or fluorescence‐activated cell sorting (FACS). Here we report the application of the Berkeley Lights Beacon Instrument (BLI) in an early SCC process to accelerate the CLD timeline. Transfected pools were single‐cell cloned when viabilities reached greater than 85% or during selection when viabilities were less than 30%. Clones isolated from these accelerated processes exhibited comparable growth, productivity, and product quality to those derived from a standard CLD process and fit into an existing manufacturing platform. With these approaches, up to a 30% reduction in the overall CLD timeline was achieved. Furthermore, early process‐derived clones demonstrated equivalent long‐term stability compared with standard process‐derived clones over 50 population doubling levels (PDLs). Taken together, the data supported early SCC on the BLI as an attractive approach to reducing the standard CLD timeline while still identifying clones with acceptable manufacturability.
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Affiliation(s)
- Jonathan Diep
- Drug Substance Technologies, Process Development, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California, USA
| | - Huong Le
- Drug Substance Technologies, Process Development, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California, USA
| | - Kim Le
- Drug Substance Technologies, Process Development, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California, USA
| | - Ewelina Zasadzinska
- Drug Substance Technologies, Process Development, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California, USA
| | - Jasmine Tat
- Drug Substance Technologies, Process Development, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California, USA
| | - Pheng Yam
- Drug Substance Technologies, Process Development, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California, USA
| | - Ryan Zastrow
- Drug Substance Technologies, Process Development, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California, USA
| | - Natalia Gomez
- Drug Substance Technologies, Process Development, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California, USA
| | - Jennitte Stevens
- Drug Substance Technologies, Process Development, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California, USA
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5
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Langsdorf E, Yu L, Kanevskaia L, Felkner R, Sturner S, McVey D, Khetan A. Retrospective assessment of clonal origin of cell lines. Biotechnol Prog 2021; 37:e3157. [PMID: 33896120 DOI: 10.1002/btpr.3157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 04/11/2021] [Accepted: 04/19/2021] [Indexed: 11/08/2022]
Abstract
Cell lines used for the manufacture of recombinant proteins are expected to arise from a single cell as a control strategy to limit variability and ensure consistent protein production. Health authorities require a minimum of two rounds of limiting dilution cloning or its equivalent to meet the requirement of single cell origin. However, many legacy cell lines may not have been generated with process meeting this criteria potentially impeding the path to commercialization. A general monoclonality assessment strategy was developed based on using the site of plasmid integration for a cell's identity. By comparing the identities of subclones from a master cell bank (MCB) to each other and that of the MCB, a probability of monoclonality was established. Two technologies were used for cell identity, Southern blot and a PCR assay based on plasmid-genome junction sequences identified by splinkerette PCR. Southern blot analysis revealed that subclones may have banding patterns that differ from each other and yet indicate monoclonal origin. Splinkerette PCR identifies cellular sequence flanking the point(s) of plasmid integration. The two assays together provide complimentary data for cell identity that enables proper monoclonality assessment and establishes that the three legacy cell lines investigated are all of clonal origin.
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Affiliation(s)
- Erik Langsdorf
- Biologics Development, Global Product Development and Supply, Bristol-Myers Squibb, New Brunswick, New Jersey, USA
| | - Le Yu
- Biologics Development, Global Product Development and Supply, Bristol-Myers Squibb, New Brunswick, New Jersey, USA
| | - Lioudmila Kanevskaia
- Biologics Development, Global Product Development and Supply, Bristol-Myers Squibb, New Brunswick, New Jersey, USA
| | - Roland Felkner
- Biologics Development, Global Product Development and Supply, Bristol-Myers Squibb, New Brunswick, New Jersey, USA
| | - Stephen Sturner
- Biologics Development, Global Product Development and Supply, Bristol-Myers Squibb, New Brunswick, New Jersey, USA
| | - Duncan McVey
- Biologics Development, Global Product Development and Supply, Bristol-Myers Squibb, New Brunswick, New Jersey, USA
| | - Anurag Khetan
- Biologics Development, Global Product Development and Supply, Bristol-Myers Squibb, New Brunswick, New Jersey, USA
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6
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Abstract
The time from discovery to proof-of-concept trials could be reduced to 5–6 months from a traditional timeline of 10–12 months.
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7
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Riba J, Schoendube J, Zimmermann S, Koltay P, Zengerle R. Single-cell dispensing and 'real-time' cell classification using convolutional neural networks for higher efficiency in single-cell cloning. Sci Rep 2020; 10:1193. [PMID: 31988355 PMCID: PMC6985245 DOI: 10.1038/s41598-020-57900-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 01/08/2020] [Indexed: 11/28/2022] Open
Abstract
Single-cell dispensing for automated cell isolation of individual cells has gained increased attention in the biopharmaceutical industry, mainly for production of clonal cell lines. Here, machine learning for classification of cell images is applied for ‘real-time’ cell viability sorting on a single-cell printer. We show that an extremely shallow convolutional neural network (CNN) for classification of low-complexity cell images outperforms more complex architectures. Datasets with hundreds of cell images from four different samples were used for training and validation of the CNNs. The clone recovery, i.e. the fraction of single-cells that grow to clonal colonies, is predicted to increase for all the samples investigated. Finally, a trained CNN was deployed on a c.sight single-cell printer for ‘real-time’ sorting of a CHO-K1 cells. On a sample with artificially damaged cells the clone recovery could be increased from 27% to 73%, thereby resulting in a significantly faster and more efficient cloning. Depending on the classification threshold, the frequency at which viable cells are dispensed could be increased by up to 65%. This technology for image-based cell sorting is highly versatile and can be expected to enable cell sorting by computer vision with respect to different criteria in the future.
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Affiliation(s)
- Julian Riba
- Cytena GmbH, Neuer Messplatz 3, 79108, Freiburg, Germany. .,Laboratory for MEMS Applications, IMTEK - Department of Microsystems Engineering, University of Freiburg, Georges-Köhler-Allee 103, 79110, Freiburg, Germany.
| | | | - Stefan Zimmermann
- Cytena GmbH, Neuer Messplatz 3, 79108, Freiburg, Germany.,Laboratory for MEMS Applications, IMTEK - Department of Microsystems Engineering, University of Freiburg, Georges-Köhler-Allee 103, 79110, Freiburg, Germany
| | - Peter Koltay
- Laboratory for MEMS Applications, IMTEK - Department of Microsystems Engineering, University of Freiburg, Georges-Köhler-Allee 103, 79110, Freiburg, Germany.,Hahn-Schickard, Georges-Koehler-Allee 103, Freiburg, 79110, Germany
| | - Roland Zengerle
- Laboratory for MEMS Applications, IMTEK - Department of Microsystems Engineering, University of Freiburg, Georges-Köhler-Allee 103, 79110, Freiburg, Germany.,Hahn-Schickard, Georges-Koehler-Allee 103, Freiburg, 79110, Germany.,BIOSS Centre for Biological Signalling Studies, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
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8
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Josephides D, Davoli S, Whitley W, Ruis R, Salter R, Gokkaya S, Vallet M, Matthews D, Benazzi G, Shvets E, Gesellchen F, Geere D, Liu X, Li X, Mackworth B, Young W, Owen Z, Smith C, Starkie D, White J, Sweeney B, Hinchliffe M, Tickle S, Lightwood DJ, Rehak M, Craig FF, Holmes D. Cyto-Mine: An Integrated, Picodroplet System for High-Throughput Single-Cell Analysis, Sorting, Dispensing, and Monoclonality Assurance. SLAS Technol 2020; 25:177-189. [DOI: 10.1177/2472630319892571] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The primary goal of bioprocess cell line development is to obtain high product yields from robustly growing and well-defined clonal cell lines in timelines measured in weeks rather than months. Likewise, high-throughput screening of B cells and hybridomas is required for most cell line engineering workflows. A substantial bottleneck in these processes is detecting and isolating rare clonal cells with the required characteristics. Traditionally, this was achieved by the resource-intensive method of limiting dilution cloning, and more recently aided by semiautomated technologies such as cell sorting (e.g., fluorescence-activated cell sorting) and colony picking. In this paper we report on our novel Cyto-Mine Single Cell Analysis and Monoclonality Assurance System, which overcomes the limitations of current technologies by screening hundreds of thousands of individual cells for secreted target proteins, and then isolating and dispensing the highest producers into microtiter plate wells (MTP). The Cyto-Mine system performs this workflow using a fully integrated, microfluidic Cyto-Cartridge. Critically, all reagents and Cyto-Cartridges used are animal component-free (ACF) and sterile, thus allowing fast, robust, and safe isolation of desired cells.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Xin Liu
- Sphere Fluidics Ltd., Cambridge, UK
| | - Xin Li
- Sphere Fluidics Ltd., Cambridge, UK
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9
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Chen C, Le K, Le H, Daris K, Soice N, Stevens J, Goudar CT. Methods for Estimating the Probability of Clonality in Cell Line Development. Biotechnol J 2020; 15:e1900289. [DOI: 10.1002/biot.201900289] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Revised: 10/20/2019] [Indexed: 12/18/2022]
Affiliation(s)
- Chun Chen
- Drug Substance TechnologiesProcess Development Amgen Inc., 1 Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Kim Le
- Drug Substance TechnologiesProcess Development Amgen Inc., 1 Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Huong Le
- Drug Substance TechnologiesProcess Development Amgen Inc., 1 Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Kristi Daris
- Drug Substance TechnologiesProcess Development Amgen Inc., 1 Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Neil Soice
- Drug Substance TechnologiesProcess Development Amgen Inc., 1 Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Jennitte Stevens
- Drug Substance TechnologiesProcess Development Amgen Inc., 1 Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Chetan T. Goudar
- Drug Substance TechnologiesProcess Development Amgen Inc., 1 Amgen Center Drive Thousand Oaks CA 91320 USA
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10
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Louie S, Heidersbach A, Blanco N, Haley B, Rose CM, Liu PS, Yim M, Tang D, Lam C, Sandoval WN, Shaw D, Snedecor B, Misaghi S. Endothelial intercellular cell adhesion molecule 1 contributes to cell aggregate formation in CHO cells cultured in serum‐free media. Biotechnol Prog 2020; 36:e2951. [DOI: 10.1002/btpr.2951] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 11/14/2019] [Accepted: 12/11/2019] [Indexed: 11/09/2022]
Affiliation(s)
- Salina Louie
- Cell Culture DepartmentGenentech, Inc. South San Francisco California
| | - Amy Heidersbach
- Molecular Biology DepartmentGenentech, Inc. South San Francisco California
| | - Noelia Blanco
- Cell Culture DepartmentGenentech, Inc. South San Francisco California
| | - Benjamin Haley
- Molecular Biology DepartmentGenentech, Inc. South San Francisco California
| | - Christopher M. Rose
- Microchemistry Proteomic and Lipidomic (MPL) DepartmentGenentech, Inc. South San Francisco California
| | - Peter S. Liu
- Microchemistry Proteomic and Lipidomic (MPL) DepartmentGenentech, Inc. South San Francisco California
| | - Mandy Yim
- Cell Culture DepartmentGenentech, Inc. South San Francisco California
| | - Danming Tang
- Cell Culture DepartmentGenentech, Inc. South San Francisco California
| | - Cynthia Lam
- Cell Culture DepartmentGenentech, Inc. South San Francisco California
| | - Wendy N. Sandoval
- Microchemistry Proteomic and Lipidomic (MPL) DepartmentGenentech, Inc. South San Francisco California
| | - David Shaw
- Cell Culture DepartmentGenentech, Inc. South San Francisco California
| | - Brad Snedecor
- Cell Culture DepartmentGenentech, Inc. South San Francisco California
| | - Shahram Misaghi
- Cell Culture DepartmentGenentech, Inc. South San Francisco California
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11
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Le K, Tan C, Le H, Tat J, Zasadzinska E, Diep J, Zastrow R, Chen C, Stevens J. Assuring Clonality on the Beacon Digital Cell Line Development Platform. Biotechnol J 2019; 15:e1900247. [DOI: 10.1002/biot.201900247] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Revised: 09/27/2019] [Indexed: 12/20/2022]
Affiliation(s)
- Kim Le
- Drug Substance TechnologiesProcess DevelopmentAmgen, Inc. One Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Christopher Tan
- Drug Substance TechnologiesProcess DevelopmentAmgen, Inc. One Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Huong Le
- Drug Substance TechnologiesProcess DevelopmentAmgen, Inc. One Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Jasmine Tat
- Drug Substance TechnologiesProcess DevelopmentAmgen, Inc. One Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Ewelina Zasadzinska
- Drug Substance TechnologiesProcess DevelopmentAmgen, Inc. One Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Jonathan Diep
- Drug Substance TechnologiesProcess DevelopmentAmgen, Inc. One Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Ryan Zastrow
- Drug Substance TechnologiesProcess DevelopmentAmgen, Inc. One Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Chun Chen
- Drug Substance TechnologiesProcess DevelopmentAmgen, Inc. One Amgen Center Drive Thousand Oaks CA 91320 USA
| | - Jennitte Stevens
- Drug Substance TechnologiesProcess DevelopmentAmgen, Inc. One Amgen Center Drive Thousand Oaks CA 91320 USA
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12
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Wang B, Albanetti T, Miro-Quesada G, Flack L, Li L, Klover J, Burson K, Evans K, Ivory W, Bowen M, Schoner R, Hawley-Nelson P. High-throughput screening of antibody-expressing CHO clones using an automated shaken deep-well system. Biotechnol Prog 2018; 34:1460-1471. [PMID: 30298994 PMCID: PMC6587815 DOI: 10.1002/btpr.2721] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 08/30/2018] [Accepted: 09/20/2018] [Indexed: 12/15/2022]
Abstract
Biopharmaceutical protein manufacturing requires the highest producing cell lines to satisfy current multiple grams per liter requirements. Screening more clones increases the probability of identifying the high producers within the pool of available transfectant candidate cell lines. For the predominant industry mammalian host cell line, Chinese hamster ovary (CHO), traditional static‐batch culture screening does not correlate with the suspension fed‐batch culture used in manufacturing, and thus has little predictive utility. Small scale fed‐batch screens in suspension culture correlate better with bioreactor processes but a limited number of clones can be screened manually. Scaled‐down systems, such as shaken deep well plates, combined with automated liquid handling, offer a way for a limited number of scientists to screen many clones. A statistical analysis determined that 384 is the optimal number of clones to screen, with a 99% probability that six clones in the 95th percentile for productivity are included in the screen. To screen 384 clones efficiently by the predictive method of suspension fed‐batch, the authors developed a shaken deep‐well plate culturing platform, with an automated liquid handling system integrating cell counting and protein titering instruments. Critical factors allowing deep‐well suspension culture to correlate with shake flask culture were agitation speed and culture volume. Using our automated system, one scientist can screen five times more clones than by manual fed‐batch shake‐flask or shaken culture tube screens and can identify cell lines for some therapeutic protein projects with production levels greater than 6 g/L. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1460–1471, 2018
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Affiliation(s)
- Benjamin Wang
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
| | - Thomas Albanetti
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
| | | | - Layla Flack
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
| | - Lina Li
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
| | - Judith Klover
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
| | - Kerri Burson
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
| | - Krista Evans
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
| | - William Ivory
- Analytical Biochemistry, MedImmune, Gaithersburg, Maryland, 20878
| | - Michael Bowen
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
| | - Ronald Schoner
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
| | - Pamela Hawley-Nelson
- Cell Culture and Fermentation Sciences, MedImmune, Gaithersburg, Maryland, 20878
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13
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Yim M, Shaw D. Achieving greater efficiency and higher confidence in single‐cell cloning by combining cell printing and plate imaging technologies. Biotechnol Prog 2018; 34:1454-1459. [DOI: 10.1002/btpr.2698] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 06/23/2018] [Accepted: 07/11/2018] [Indexed: 12/22/2022]
Affiliation(s)
- Mandy Yim
- Cell Culture, Pharma Technical DevelopmentGenentech, Inc. 1 DNA Way South San Francisco California, 94080
| | - David Shaw
- Cell Culture, Pharma Technical DevelopmentGenentech, Inc. 1 DNA Way South San Francisco California, 94080
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